RETIN AL: An Active Learning Strategy for Image Category Retrieval

Philippe-Henri Gosselin (1) , Matthieu Cord (2)

1 MIDI - Multimedia Indexation and Data Integration
2 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes

Active learning methods have been considered with an increasing interest in the content-based image retrieval (CBIR) community. In this article, we propose an effi- cient method based on active learning strategy to retrieve large image categories. At each feedback step, the system optimizes the image set presented to the user in order to speed up the retrieval. Experimental tests on COREL photo database have been carried out.

Domains: Machine Learning [stat.ML]

Philippe-Henri Gosselin, Matthieu Cord. RETIN AL: An Active Learning Strategy for Image Category Retrieval. IEEE International Conference on Image Processing,, Oct 2004, Singapore. pp.1. ⟨hal-00520315⟩